The present invention relates to radiation therapy for the treatment of cancer and the like and, in particular, to a planning method and to an apparatus for radiation therapy using implanted radioactive sources.
Prostate implant brachytherapy is a radiation treatment technique in which radioactive sources are implanted directly into the prostate and either moved or removed after a period of time or left in place permanently. For permanent brachytherapy, typically 44 to 100 small radioactive sources are implanted near the tumorous tissue. Temporary brachytherapy is where sources are inserted into or near tissue to be treated, left in place for hours or days, and then removed. High dose-rate implants refer to a special case of temporary implants where the catheters are implanted in the treatment target and a single movable high dose-rate source is made to dwell (for times ranging between 0.1 s to a few minutes) at various locations in the tumorous tissue, delivering the dose in less than one hour. While treatment of prostate cancer is used as an example, nothing about this invention limits it use to that body site or disease.
The sources may be a radioactive material adsorbed onto small resin spheres or other carriers contained within a titanium capsule or on the surface of a silver rod also sealed in titanium. Depending on the radionuclide used, the sources typically have a half-life of approximately 3 to 180 days, but not limited to that range, providing an average energy of emitted photons of approximately, but not limited to 20 to 600 keV with a typical commercial source strength in the range of 0.1-5 mCi for permanent implants and approximately 10 Ci for high dose-rate sources, although other strengths may be used. Example radionuclides used are 125I, 103Pd or 131Cs for permanent brachytherapy and 192Ir for high dose rate brachytherapy, or 192Ir or 125I for temporary low dose-rate applications. Other radionuclides may also be used. The sources may be generally isotropic, having uniform radiation patterns (e.g. radially symmetric about the source), or may be anisotropic or directional, for example by incorporating small shields into the source that focus the radiation pattern in one direction.
In permanent low dose rate brachytherapy, the sources are of a size, e.g., 0.8 mm in diameter and 4.5 to 5 mm long, so that they may be implanted using a hollow needle. The needle provides a lumen 1.3 to 1.5 millimeters in diameter and about twenty centimeters long into which sources may be inserted along with spacers controlling their separation. The loaded needle is inserted into the patient and then withdrawn while a plunger ejects the contained sources.
Placement of the sources, for example, for use in treatment of the prostate may be done transperineally and the needles are guided by a plate having predrilled holes on a regular grid. The depth of insertion of the needles is normally guided by an image obtained with a transrectal ultrasonic imaging device. In this way, sources may be accurately placed at selected regular grid locations.
In temporary implants using high dose rate brachytherapy, a small source with dimensions 0.7 mm diameter and 3-4 mm in length is welded to the tip of a flexible stainless steel cable, which travels in and out of the hollow catheters with dwell positions at every 5 mm interval. A source moves in steps through the catheters, stopping at selected dwell positions for a pre-calculated amount of time to deliver the required radiation dose.
The locations of the radioactive sources along the grid or dwell locations and corresponding dwell time along the catheters are desirably selected to provide the prescribed dose to the diseased tissue of the prostrate while sparing surrounding sensitive critical tissue, for example, the urethra and rectum. Such selection/placement is aided by treatment planning performed before the implantation of the sources.
In current practice, treatment planning is largely trial and error based on some simple spacing rules after an inspection of the tumor site by ultrasonic or other imaging techniques. More precise treatment planning may be obtained by a number of well known optimization processes providing mathematical simulation of a dose from a given source pattern.
Determining the dose produced by “forward” calculations, i.e., from a given pattern of sources is a relatively straightforward process, however, the “backwards” calculation from the desired dose to a source pattern is mathematically difficult. Such problems are typically addressed by stochastic techniques, such as “simulated annealing” or by “genetic algorithms” that perform repeated forward calculations for many possible source patterns and then apply an objective function to dose produced by the pattern to select the best pattern.
A deterministic approach to treatment planning is provided by the “branch and bound” method described, for example, in “Treatment Planning for Brachytherapy: An Integer Programming Model, Two Computational Approaches and Experiments With Permanent Prostate Implant Planning”, by Lee E. K. et al., Phys. Med. Biol. 44: 145-165 (1999), and “An Iterative Sequential Mixed-Integer Approach to Automated Prostate Brachytherapy Treatment Plan Optimization”, D'Souza W. D. et al., Phys. Med. Biol. 46: 297-322 (2001).
Operating on high-speed computers, these approaches may take minutes to more than half an hour to complete for a typical prostate treatment plan and may also involve varying degrees of manual intervention. Such delay imposes considerable inconvenience and expense on a patient, either in waiting for the implant during the treatment planning process, or in having to return after the treatment planning session at a later date for the implanting or in paying for the Operation Room time involved in the procedure. Manual intervention makes treatment planning a subjective task and reproducibility of the same quality implants becomes a matter of concern. In addition, the time involved in such feedback oriented and trial and error based optimization techniques make the treatment planning inappropriate for application into intraoperative or interactive brachytherapy where the treatment plan needs to be generated inside the operation theater with the patient in treatment position. With patient under anesthesia, every minute added to the delay in treatment planning counts. Availability of a fast as well as reliable treatment planning technique therefore, holds utmost importance.
The parent application to the present application describes an improved treatment planning technique in which an “importance function” is precomputed and then used without modification to locate sources in a sequential process in which the sources are not repositioned after they are located. An exclusion zone is placed around each source to prevent this sequential placement from producing clusters of sources in the high importance areas at the expense of other portions of the tumor. By using a “greedy” algorithm, processing time is substantially decreased.
A greedy algorithm is any algorithm that follows the strategy of making a locally optimum choice at each stage with the hope of finding the global optimum. The greedy heuristic method for treatment planning optimization is fundamentally different from other dynamic optimization methods, such as simulated annealing, genetic algorithm and branch and bound method. The choice made by a greedy algorithm may depend on choices already made but not on future choices or of the solutions to the sub-problem. It sequentially makes one greedy choice after another, reducing each given problem into a smaller one. In other words, a greedy algorithm never reconsiders its choices.
This is the main difference from dynamic programming. After every stage, dynamic programming makes decisions based on all the decisions made in the previous stage, and may reconsider the previous stage's algorithmic path to solution.
Another difference between the dynamic programming and the greedy is that dynamic programming is exhaustive and is often guaranteed to find the optimum solution, whereas the greedy provides a good, near optimum solution for must problems and the optimum for a few problems.